license: mit
library_name: libreyolo
pipeline_tag: depth-estimation
tags:
- image-to-image
- surface-normals
- moge
LibreMoGe3l-normal
MoGe-3 ViT-L/14 for surface-normal estimation, repackaged in LibreYOLO checkpoint format.
Source
Derived from Ruicheng/moge-3-vitl model.pt
at revision 184008f877d7ad1ad4c2cd2182a9bd1f63d0e5be, the exact commit LibreYOLO pins. The source model card
declares these weights MIT.
Copyright (c) Microsoft Corporation. Code: microsoft/MoGe
at 74fbce054ebed49800de42d0ad0e83495065719a, MIT License.
The DINOv2 encoder MoGe-3 builds on is separately licensed Apache-2.0 by
Meta AI; both notices are preserved in MoGe's composite LICENSE, copied
verbatim here.
Modifications
None to the learned parameters: every tensor of the official checkpoint is
kept unchanged, and LibreYOLO checkpoint v1.0 metadata (task normal) is
added. The same tensors serve the depth and normal tasks. See
weights/convert_moge3_weights.py in the
LibreYOLO source repository.
Usage
from libreyolo import LibreYOLO
model = LibreYOLO("LibreMoGe3l-normal.pt")
result = model.predict("image.jpg")
normals = result.normals # (H, W, 3) OpenCV-frame unit normals
License
MIT License. See the LICENSE and NOTICE files in
this repository.